四川轻化工大学学报（自然科学版）2026，Vol.39Issue(1)：54-61,8.DOI:10.11863/j.suse.2026.01.06
一种改进CFL-Net的图像篡改检测算法
An Improved Image Tampering Detection Algorithm Based on CFL-Net
摘要
Abstract
With the rapid advancement of information technology,the issue of image tampering has become increasingly prominent across various fields,making image tampering detection technology increasingly vital for safeguarding the authenticity of information.To address the current issues in image tampering detection algorithms,such as insufficient feature fusion and limited ability to capture key features of tampered regions,an improved image tampering detection algorithm based on CFL-Net is proposed.An Squeeze-and-Excitation(SE)module is added to the original ResNet-50 feature extraction network to enhance the model's focus on tampering features.Additionally,an Attentional Feature Fusion(AFF)module is introduced to fuse features from the RGB and noise branches,enabling effective complementary fusion of the dual-branch features.An edge loss function is also incorporated to help the model focus on the edge information of tampered regions.Results show that,compared to U-Net,PSCC-Net,MVSS-Net,and CFL-Net,the improved algorithm performs well across five widely used datasets,demonstrating superior detection and localization capabilities.关键词
图像篡改检测/注意力机制/特征融合/特征提取Key words
image tampering detection/attention mechanism/feature fusion/feature extraction分类
信息技术与安全科学引用本文复制引用
刘胜波,何小利..一种改进CFL-Net的图像篡改检测算法[J].四川轻化工大学学报（自然科学版）,2026,39(1):54-61,8.基金项目
2024教育部第三期供需对接就业育人项目(2023122021680) （2023122021680）
视频图像篡改检测算法开发项目(E10204710) （E10204710）
自贡市重点科技计划项目(自贡市医学大数据与人工智能研究院)(2022ZCYGY16) （自贡市医学大数据与人工智能研究院）
企业信息化与物联网测控技术四川省高校重点实验室项目(2022WYY02) （2022WYY02）
四川轻化工大学教学改革研究项目(JG-24025) （JG-24025）
